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To the editor:
Many BCR-ABL1 compound mutations reported in chronic myeloid leukemia patients may
actually be artifacts due to PCR-mediated recombination
BCR-ABL1 kinase domain (KD) mutations are the most common
known cause of treatment failure in chronic myeloid leukemia
(CML). Emerging evidence suggests that compound mutations
(.1 KD mutation in the same molecule) confer resistance to
ponatinib1,2 and combination therapy (GNF-5/nilotinib).3 Several
recent studies, including 2 published in Blood, employed nested
polymerase chain reaction (PCR) amplification of the BCR-ABL1
KD, followed by cloning and Sanger sequencing4 or next-generation
sequencing,5,6 and found a high incidence of compound mutations in
imatinib-resistant CML patients with multiple KD mutations. These
studies would imply that even a combination approach to therapy
would be futile in this setting. Furthermore, they argue strongly
against the sequential use of different tyrosine kinase inhibitors in
high-risk settings. Surprisingly, however, in most cases reported,
the same mutations were found both as compound mutations and
as individual mutations in the same patient,4-6 suggesting that the
same nucleotide substitution occurred independently multiple
times within an individual patient. This complexity is difficult to
explain phylogenetically. Based on extensive evidence that PCR
frequently mediates recombination between highly similar templates
Figure 1. PCR artifacts may mimic BCR-ABL1 compound mutations in CML patients. (A) Outline of the experimental procedure used. Experiment type 1 controls for
recombination during cloning into Escherichia coli; mutant BCR-ABL1 plasmids were subjected to PCR amplification individually, and then equal quantities of amplicons of 2
plasmids were mixed, denatured by heating to 95°C for 5 minutes, and cloned. Experiment type 2 mimics amplification of samples from patients with $2 mutant BCR-ABL1
clones; equal quantities of 2 plasmids were mixed and subjected to PCR amplification and cloning. Both types of experiments were replicated using 7 mixtures of 5 different
plasmids, each containing 4 to 10 KD mutations. Approximately 3000 copies of each plasmid were used as template for each PCR. Unless otherwise specified, first-round
PCR (40 cycles) was performed using the Roche Expand Long Template PCR System and the primers 59-TGACCAACTCGTGTGTGAAACTC-39 and 59TTCGTCTGAGATACTGGATTCCTG-39, generating ;1.5 kb amplicons. After cleanup with ExoSAP-IT (Affymetrix), 1 mL of the amplicons was used as template in
a second-round PCR (40 cycles) using the primers 59-GGGCTCTATGGGTTTCTGAATG-39 and 59-ATACTGGATTCCTGGAACATTGTTT-39, generating ;1.5 kb amplicons
containing the BCR-ABL1 KD. Amplified fragments were cloned into pGEM-T Easy (Promega, Madison, WI) and transformed into E coli strain JM109 to minimize
Ecoli–mediated recombination and repair of heterologous DNA. Individual clones (14-37 per mixture) were subjected to Sanger sequencing to reveal the BCR-ABL1 KD
sequence within individual amplicons. Clones without artificial recombination are those where the KD mutations resemble those in either of the plasmids in the mixture, and
conversely clones with artificial recombination are those with KD mutations originating from both of the plasmids in the original mixture. (B) The KD mutations potentially
generated in clones if artificial recombination did not (i, iii) or did (ii, iv) occur. Circles represent compound mutations in plasmid X, and boxes represent compound mutations in
plasmid Y; hexagons represent E255K (mix 1, first patient), and stars represent T315I (mix 1, second patient). (C) Sanger sequencing chromatograms showing KD mutations
present in a representative plasmid X (black circles) and plasmid Y (gray boxes) and a clone generated using the experiment type 2 procedure. This clone contained 2 of 3
mutations originating from plasmid X as well as 1 mutation originating from plasmid Y. The artificial recombination event occurred within the region marked by the hashed bar.
(D) Artificial BCR-ABL1 compound mutations are generated by PCR amplification of mock samples created by mixing equal quantities of cDNA from 8 different CML patients
(analogous to experiment type 2; 3 mixtures of 2-3 patient cDNA samples each). Where human tissue was involved, research was conducted with institutional ethics review
board approval and in conformance with the Declaration of Helsinki. Mutations present in the original patient samples are shown in bold. Mutations present in .1 clone, but not
detected by Sanger sequencing or mass spectrometry in the individual patient samples (“additional mutations”), are shown in regular text; with the exception of exon 7
deletion, these mutations have not been reported in CML patients and likely represent artifacts generated by inaccurate nucleotide incorporation by the DNA polymerase. The
frequency of each clone is shown in proportion to the number of clones sequenced per mixture. A total of 13 different clones were detected for mix 1, 5 different clones for mix
2, and 7 different clones for mix 3.
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154
BLOOD, 3 JULY 2014 x VOLUME 124, NUMBER 1
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Figure 1. (Continued)
and generates chimeric amplicons containing sequence from .1
different alleles,7-9 we argue that the mutant complexity reported may
be inflated due to PCR artifacts.
We replicated published procedures4 using mock samples created by
mixing mutant BCR-ABL1 plasmids or patient samples, mimicking
patients with .1 polyclonal mutant (Figure 1A). When plasmids were
PCR amplified singly, and the amplicons of 2 plasmids were mixed,
denatured, and cloned (experiment type 1), sequencing of individual
clones revealed KD mutations that largely resembled those present in
either of the starting plasmids. However, when the plasmids were mixed
before PCR amplification (experiment type 2), a large proportion of
the resultant clones had KD mutations that originated from both of
the starting plasmids (depicted in Figure 1B-C), suggesting that
recombination had occurred during PCR amplification. We repeated
this using 7 mixtures of 5 different plasmids and found that 20% to
67% of clones showed evidence of artificial recombination resulting
in compound mutations that were not present in the starting material,
compared with 3% in the control experiments (P , .001).
No hot-spot regions were observed for recombination events.
Recombination events occurred at similar frequency using several
DNA polymerases: 39% with Roche Expand Long (9/23 clones
showed artificial recombination), 29% with Roche FastStart (7/24
clones), and 38% with NEB Q5 (13/34 clones). Single-round PCR
(35 cycles) using Roche Expand Long significantly reduced
recombination events compared with nested PCR using the same
enzyme (0% [0/21]; P 5 .0016).
The procedure was replicated with 3 mock samples created by
mixing complementary DNA (cDNA) from 8 patients, each with 1 KD
mutation detected by direct Sanger sequencing and sensitive mass
spectrometry.10 Artificial compound mutations were detected in clones
of all mixtures, including E255K/T315I compound mutation predicted
to confer resistance to ponatinib (Figure 1D). Additional mutations, not
present in any of the patient samples, were detected in some clones,
suggesting that inaccurate nucleotide incorporation by the DNA
polymerase also contributes to artifact mutations.
Our study demonstrates that PCR artifacts may mimic BCRABL1 compound mutations, leading to inaccurate assessment of
mutation status, which could have serious clinical consequences
for patients. We urge caution when interpreting results using
current procedures and call for new techniques to more reliably
detect compound mutations and differentiate them from multiple
polyclonal mutations. This will enable r7ational adjustment to the
therapeutic approach and more accurate assessment of the impact
of various mutations on patient outcome.
Wendy T. Parker
Department of Genetics and Molecular Pathology,
Centre for Cancer Biology, SA Pathology,
Adelaide, Australia
School of Pharmacy and Medical Science,
University of South Australia,
Adelaide, Australia
Stuart R. Phillis
Department of Genetics and Molecular Pathology,
Centre for Cancer Biology, SA Pathology,
Adelaide, Australia
David T. O. Yeung
Departments of Genetics and Molecular Pathology and Hematology,
Centre for Cancer Biology, SA Pathology,
Adelaide, Australia
School of Medicine, University of Adelaide,
Adelaide, Australia
Timothy P. Hughes
Department of Hematology, Centre for Cancer Biology, SA Pathology,
Adelaide, Australia
School of Medicine, University of Adelaide,
Adelaide, Australia
Cancer Theme, South Australian Health and Medical Research Institute,
Adelaide, Australia
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BLOOD, 3 JULY 2014 x VOLUME 124, NUMBER 1
Hamish S. Scott
Department of Genetics and Molecular Pathology,
Centre for Cancer Biology, SA Pathology,
Adelaide, Australia
Schools of Medicine and Molecular and Biomedical Science,
University of Adelaide,
Adelaide, Australia
School of Pharmacy and Medical Science,
University of South Australia,
Adelaide, Australia
Susan Branford
Department of Genetics and Molecular Pathology,
Centre for Cancer Biology, SA Pathology,
Adelaide, Australia
Schools of Medicine and Molecular and Biomedical Science,
University of Adelaide,
Adelaide, Australia
School of Pharmacy and Medical Science,
University of South Australia,
Adelaide, Australia
Acknowledgments: This work was supported by National Health and Medical
Research Council of Australia grant 1027531 (S.B., H.S.S., and T.P.H.) and
fellowship 1023059 (H.S.S.), a Leukaemia Foundation of Australia/Cure
Cancer Australia postdoctoral fellowship (W.T.P.), and a Leukaemia
Foundation of Australia and AR Clarkson PhD scholarship (D.T.O.Y.).
The Centre for Cancer Biology is an alliance between SA Pathology and the
University of South Australia.
Contribution: W.T.P. contributed to experimental design, performed research,
analyzed data, and wrote the manuscript; S.R.P. performed research; D.T.O.Y.,
H.S.S., and S.B. contributed to experimental design and manuscript
preparation; and T.P.H. contributed to manuscript preparation.
Conflict-of-interest disclosure: S.B. and T.P.H. receive research funding and
honoraria from Novartis Pharmaceuticals, Bristol-Myers Squibb, and Ariad
Pharmaceuticals. D.T.O.Y. receives research funding and honoraria from
CORRESPONDENCE
155
Novartis Pharmaceuticals and Bristol-Myers Squibb. The remaining authors
declare no competing financial interests.
Correspondence: Wendy Parker, Department of Genetics and Molecular
Pathology, Centre for Cancer Biology, SA Pathology, Frome Rd, Adelaide SA
5000, Australia; e-mail: [email protected].
References
1. Gibbons DL, Pricl S, Posocco P, et al. Molecular dynamics reveal BCR-ABL1
polymutants as a unique mechanism of resistance to PAN-BCR-ABL1 kinase
inhibitor therapy. Proc Natl Acad Sci U S A. 2014;111(9):3550-3555.
2. O’Hare T, Shakespeare WC, Zhu X, et al. AP24534, a pan-BCR-ABL inhibitor
for chronic myeloid leukemia, potently inhibits the T315I mutant and overcomes
mutation-based resistance. Cancer Cell. 2009;16(5):401-412.
3. Zhang J, Adrián FJ, Jahnke W, et al. Targeting Bcr-Abl by combining allosteric
with ATP-binding-site inhibitors. Nature. 2010;463(7280):501-506.
4. Khorashad JS, Kelley TW, Szankasi P, et al. BCR-ABL1 compound mutations in
tyrosine kinase inhibitor-resistant CML: frequency and clonal relationships.
Blood. 2013;121(3):489-498.
5. Kastner R, Zopf A, Preuner S, et al. Rapid identification of compound mutations
in patients with Philadelphia-positive leukaemias by long-range next generation
sequencing. Eur J Cancer. 2014;50(4):793-800.
6. Soverini S, De Benedittis C, Machova Polakova K, et al. Unraveling the
complexity of tyrosine kinase inhibitor-resistant populations by ultra-deep
sequencing of the BCR-ABL kinase domain. Blood. 2013;122(9):1634-1648.
7. Meyerhans A, Vartanian JP, Wain-Hobson S. DNA recombination during PCR.
Nucleic Acids Res. 1990;18(7):1687-1691.
8. Bradley RD, Hillis DM. Recombinant DNA sequences generated by PCR
amplification. Mol Biol Evol. 1997;14(5):592-593.
9. Kanagawa T. Bias and artifacts in multitemplate polymerase chain reactions
(PCR). J Biosci Bioeng. 2003;96(4):317-323.
10. Parker WT, Lawrence RM, Ho M, et al. Sensitive detection of BCR-ABL1 mutations
in patients with chronic myeloid leukemia after imatinib resistance is predictive of
outcome during subsequent therapy. J Clin Oncol. 2011;29(32):4250-4259.
© 2014 by The American Society of Hematology
To the editor:
The effect of low-molecular-weight heparin in cancer patients: the mirror image of survival?
The use of low-molecular-weight heparin (LMWH) during anticancer therapy has been studied by several authors, who speculated
about a direct antitumor effect of LMWH, which might be translated
into a survival benefit in patients with cancer.1 Other authors have
suggested that the antitumor activity of LMWH was fortuitous and
independent of the anticoagulant effect.2
According to this theory, the advantage in terms of survival
should be weighted differently if one is evaluating the anticancer
or antithrombotic effects of LMWH.2
Based on this assumption, we conducted a post hoc analysis of
the PROTECHT (PROphylaxis of ThromboEmbolism during
CHemoTherapy; #NCT00951574) study3 to evaluate if prophylaxis
with nadroparin conferred any additional benefit in terms of survival,
depending on whether chemotherapy disease control was achieved
(complete response, partial response, or stable disease).
In the PROTECHT study, nadroparin (3800 anti-Xa IU once
daily for 120 days) has been demonstrated to reduce the incidence of
venous and arterial thrombotic events by about 50% in 1150 cancer
outpatients receiving chemotherapy (P 5 .024).
In our post hoc analysis, individual patient data were reviewed and
analyzed to assess response to chemotherapy and overall survival.
Overall survival was calculated 1 year after study treatment (nadroparin
or placebo) initiation by considering the time from randomization to
the occurrence of death or last follow-up visit if the event did not
occur (right censored). Survival analysis was performed using a Cox
regression model with treatment (nadroparin or placebo), response to
chemotherapy (disease control or no disease control), and their interaction as covariates. A statistically significant interaction indicates
Figure 1. Survival curves for the Cox model estimated based on the Breslow
approach.
From www.bloodjournal.org by guest on June 16, 2017. For personal use only.
2014 124: 153-155
doi:10.1182/blood-2014-05-573485
Many BCR-ABL1 compound mutations reported in chronic myeloid
leukemia patients may actually be artifacts due to PCR-mediated
recombination
Wendy T. Parker, Stuart R. Phillis, David T. O. Yeung, Timothy P. Hughes, Hamish S. Scott and
Susan Branford
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